Governance: A Source to Increase Tax Revenue in Pakistan

Hassan, Muhammad Shahid; Mahmood, Haider; Tahir, Muhammad Naveed; Alkhateeb, Tarek Tawfik Yousef; Wajid, Ayesha

doi:10.1155/2021/6663536

Cited by 19 publications

(11 citation statements)

References 36 publications

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“…e asset expropriation mainly belongs to family firms, which shows the tunneling behavior of family firms. e overall level of country governance is relatively low in Pakistan [9]. Furthermore, the regulatory bodies are struggling to enforce corporate governance mechanism in Pakistan.…”

Section: Introductionmentioning

confidence: 99%

Board Financial Expertise and Corporate Cash Holdings: Moderating Role of Multiple Large Shareholders in Emerging Family Firms

Um-e-Habiba

Husnain³

et al. 2021

Complexity

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This study contributes to the literature by exploring the relationship between board financial expertise and cash holding policy and further showing how this relation is moderated by multiple large shareholders (MLS). This research is based on agency theory, resource dependence, trade-off, and pecking order theory to confirm how resourceful directors screen cash holding practices. This study selects the 100 listed family firms from the emerging economy of Pakistan for the period of 2006–2017. With the use of static (random and fixed effect estimator) and dynamic (GMM) estimation techniques, this study reveals that the financial expertise of the board members has a significant negative impact on the firms’ cash holding level. Further, moderating effect of MLS between board financial expertise and cash holding is significantly positive due to weak corporate governance mechanisms in family firms. Moreover, the research has implications for developing corporate governance mechanism and the management of liquid assets that corporate management might use for their benefits.

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Section: Introductionmentioning

confidence: 99%

Board Financial Expertise and Corporate Cash Holdings: Moderating Role of Multiple Large Shareholders in Emerging Family Firms

Um-e-Habiba

Husnain³

et al. 2021

Complexity

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“…In this research, double log form approach is considered for estimating robust results as exposed by many scholars like M. S. Hassan et al ( , 2015Hassan et al ( , 2016Hassan et al ( , 2018Hassan et al ( , 2021, Mamoon et al (2017), Iftekhar et al (2016aIftekhar et al ( , 2016b, Kalim and Hassan (2014), Satti et al (2014), Ehrlich (1977), Layson (1983), Bowers and Pierce (1975), Cameron (1994), and Ehrlich (1996) in their researches. They were of the view that the results are robust, efficient, and consistent if these are calculated by using double log transformation approach.…”

Section: Functional Form Of the Studymentioning

confidence: 99%

Investigating Export Determinants: A Time Series Evidence From Canada

2022

Self Cite

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Export is an important macroeconomic factor that can elevate a country’s output performance and raise employment opportunities, in any economy. Any country may expand the number of its allies through exports. Foundation trade theories, like absolute advantage and comparative advantage, suggest that a country should export the product with greater absolute or comparative advantage. This sheds light on allocating the optimal resources for producing low-price products and flouting the idea of specialization among the countries of the world. The present study explores the factors that may influence the export performance of a developed economy like Canada from 1979 to 2019. The study findings provide evidence of the absence of multicollinearity and that the data series for the selected functional form of the study is stationary at mixed order. The results of the ARDL bounds test confirm long-run cointegrating relations between exports and its determinants for Canada. The results further reveal that per capita energy consumption and government final consumption expenditures significantly elevate export performance in both the long and short run, while population size significantly elevates exports performance only in the long run in Canada. Moreover, the findings also expose that real effective exchange rate significantly reduces exports in both the long and short run in Canada: This means that by depreciating Canadian currency, Canadian exports will be boosted. The real interest rate reports a negative but insignificant impact on the Canadian export function in both the long and short run. Finally, the CUSUM and CUSUM Square graphs confirm the stability of the estimated coefficients for the Canadian export function for the selected sample of the study.

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“…From the perspective of tax audit practice, Tarfa et al (2020) analyzed the effect of tax audit on revenue generation using panel regression, and the results showed that illegal practice of taxpayers was a significant and negative factor that affected tax revenue generation and that the objective of tax audit, audit technique, and training for taxpayers were significant and positive factors. Hassan et al (2021) examined the relationship between governance and tax revenue collection, discovered external conflicts to remarkably have the largest effect on tax revenue.…”

Section: Literature Reviewmentioning

confidence: 99%

Machine Learning Analytics for Predicting Tax Revenue Potential

2022

Journal ITRev

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In line with rapid business process digitalization in the Directorate General of Taxes, the size of the data stored in the institution has grown exponentially. However, there is a problem with generating value out of the valuable data assets. Correspondingly, this research provides machine-learning-based predictive analytics as a solution to the question of how to use taxpayers' trigger data as a decision support system to discover and realize unexplored tax potential. More specifically, this research presents predictive analytics models that can accurately predict which potential taxpayers are likely to pay their due. We developed three machine learning models: logistic regression, random forest, and decision tree. We analyzed 5,562 tax revenue potential data samples with eight predictors: trigger data nominal value, distance to tax office, type of taxpayer, media of tax report, type of tax, report status, registered year of taxpayer, and area coverage. Our study shows that the random forest model provided the best prediction performance. The resultant weight of each attribute indicated that the status of the tax report was the top tier of variable importance in predicting tax revenue potential. The analytics can help tax officers determine potential taxpayers with the highest likelihood to pay their due. Given the size of the data records, this approach can provide tax administrators with a powerful tool to increase work efficiency, combat tax evasion, and provide better customer service.

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Governance: A Source to Increase Tax Revenue in Pakistan

Cited by 19 publications

References 36 publications

Board Financial Expertise and Corporate Cash Holdings: Moderating Role of Multiple Large Shareholders in Emerging Family Firms

Board Financial Expertise and Corporate Cash Holdings: Moderating Role of Multiple Large Shareholders in Emerging Family Firms

Investigating Export Determinants: A Time Series Evidence From Canada

Machine Learning Analytics for Predicting Tax Revenue Potential

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